Description
Description
Who You Are
You are a quantitative thinker who wants to develop further as both a data scientist and an engineer. You are excited to grow your existing expertise in fields such as statistics and computer science alongside a diverse team of researchers, test designers, and software engineers. You are passionate about maintaining the high scientific and engineering standards required to enable your peers. Above all, you are a curious problem solver who thrives being on the critical path solving complex analytical tasks and building efficient, transparent, data pipelines.
Who We Are
SAIC is looking for a Data Scientist to help the Identity and Data Sciences Laboratory (IDSL) which is tasked with identifying state-of-the-art technologies including facial recognition and AI, evaluating performance, and examining their applicability to existing or emerging customer use cases. The IDSL has a cutting-edge infrastructure consisting of both on-prem distributed computing clusters and cloud based analytic environments, which we use for gathering and processing multi-modal data in real-time from large-scale experiments conducted at our test facility (Maryland Test Facility; http://mdtf.org), in field locations, as well as from external data sources.
Hybrid - 3 Days in Office / 2 Days Remote
What You Will Be Doing
- Contribute to data acquisition, management, and processing tasks, working with senior data scientists, software engineers and evaluation designers to build efficient data pipelines
- Access available infrastructure, and to develop analytic products tailored to mission user requirements
- Work with senior team members to organize, clean, migrate and process datasets with advanced computer vision algorithms
Qualifications
Requirements:
- Ability to obtain and maintain a public trust requiring US Citizenship
- A bachelor's degree in computer science, data science, or a comparative quantitative science or scheduled to obtain one by spring or summer 2026
- Proficient in programming (Python, C++, Golang, Java, etc.)
- Familiar with machine learning, data mining, and/or statistics (R, Python, etc.)
- Familiar with source control (e.g., Git)
- Familiar with common data formats (JSON, Parquet, XML, etc.)
- Familiar with database technologies (SQL, NoSQL)
Desired Skills:
- Prior experience related to data engineering, data science, data architecture, and databases
- Understanding of scaling and performance of distributed/cloud systems (AWS)
- Understanding of data science concepts, AI/ML, automation, and scripting
- Experience with techniques and platforms to manage, manipulate, and draw insight from large datasets (Spark, Hadoop, Databricks, etc.)
- Strong communication skills, with the ability to present findings and recommendations to both technical and non-technical audience
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